summarize_stats: Compute mean, sd, and CV for all Peptides, or proteins, for...

In wolski/prolfqua: Proteomics Label Free Quantification

Compute mean, sd, and CV for all Peptides, or proteins, for all interactions and all samples.

Description

Compute mean, sd, and CV for all Peptides, or proteins, for all interactions and all samples.

Compute mean, sd, and CV for e.g. Peptides, or proteins, for all samples.

summarize stats output (compute quantiles)

Usage

summarize_stats(pdata, config, factor_key = config$table$factor_keys_depth())

summarize_stats_all(pdata, config)

summarize_stats_quantiles(
  stats_res,
  config,
  stats = c("sd", "CV"),
  probs = c(0.1, 0.25, 0.5, 0.75, 0.9)
)

Arguments

pdata	data.frame
config	AnalysisConfiguration
stats_res	result of running 'summarize_stats'
stats	summarize either sd or CV
probs	for which quantiles 10, 20 etc.
all	also compute for all samples (default), or only of conditions (set to FALSE)

See Also

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_proteins(), lfq_power_t_test_quantiles(), lfq_power_t_test_quantiles_V2(), plot_stat_density(), plot_stat_density_median(), plot_stat_violin(), plot_stat_violin_median(), plot_stdv_vs_mean(), pooled_V2()

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_proteins(), lfq_power_t_test_quantiles(), lfq_power_t_test_quantiles_V2(), plot_stat_density(), plot_stat_density_median(), plot_stat_violin(), plot_stat_violin_median(), plot_stdv_vs_mean(), pooled_V2()

Other stats: INTERNAL_FUNCTIONS_BY_FAMILY, lfq_power_t_test_proteins(), lfq_power_t_test_quantiles(), lfq_power_t_test_quantiles_V2(), plot_stat_density(), plot_stat_density_median(), plot_stat_violin(), plot_stat_violin_median(), plot_stdv_vs_mean(), pooled_V2()

Examples

bb <- prolfqua::sim_lfq_data_protein_config()
config <- bb$config
data <- bb$data

res1 <- summarize_stats(data, config)

res2 <- prolfqua::sim_lfq_data_2Factor_config()
res2$config$table$factorDepth <- 2
stats <- summarize_stats(res2$data, res2$config)
stopifnot(nrow(stats) == 40)

stats <- summarize_stats(res2$data, res2$config, factor_key = res2$config$table$factor_keys()[1])
stopifnot(nrow(stats) == 20)
stats <- summarize_stats(res2$data, res2$config, factor_key = res2$config$table$factor_keys()[2])
stopifnot(nrow(stats) == 20)
stats <- summarize_stats(res2$data, res2$config, factor_key = NULL)
stopifnot(nrow(stats) == 10)



bb <- prolfqua::sim_lfq_data_protein_config()

res1 <- summarize_stats_all(bb$data, bb$config)

stopifnot((res1 |> dplyr::filter(group_ == "All") |> nrow()) == (res1 |> nrow()))
res2 <- prolfqua::sim_lfq_data_2Factor_config()
resSt <- summarize_stats_all(res2$data, res2$config)
library(ggplot2)
bb1 <- prolfqua::sim_lfq_data_peptide_config()
config <- bb1$config
data <- bb1$data
stats_res <- summarize_stats(data, config)
sq <- summarize_stats_quantiles(stats_res, config)
sq <- summarize_stats_quantiles(stats_res, config, stats = "CV")
bb <- prolfqua::sim_lfq_data_peptide_config()
config <- bb$config
data <- bb$data
config$table$get_response()
stats_res <- summarize_stats(data, config)
sq <- summarize_stats_quantiles(stats_res, config)
sq <- summarize_stats_quantiles(stats_res, config, stats = "sd")
stats_res <- summarize_stats(data, config)
xx <- summarize_stats_quantiles(stats_res, config, probs = seq(0,1,by = 0.1))
ggplot2::ggplot(xx$long, aes(x = probs, y = quantiles, color = group_)) + geom_line() + geom_point()

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.